ArticleOncology letters2019
Breast cancer survival prediction using seven prognostic biomarker genes.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The prognostic influence of lymphatic endothelium-specific hyaluronan receptor 1 in cancer: A systematic review.Cancer science · 2022Pooled it
- Trial
- The potential of mitochondrial permeability transition-driven necrosis-related genes in prognostic evaluation of colorectal cancer patients.Frontiers in oncology · 2026Article
- BRCAGenie: A machine learning-driven 43-gene polygenic risk score model for precision prediction of breast cancer survival.Journal of translational medicine · 2025Article
- Article
- Prognostic signatures of sphingolipids: Understanding the immune landscape and predictive role in immunotherapy response and outcomes of hepatocellular carcinoma.Frontiers in immunology · 2023Article
- Privacy-aware multi-institutional time-to-event studies.PLOS digital health · 2022Article
- Feature screening for survival trait with application to TCGA high-dimensional genomic data.PeerJ · 2022Article
- Identification of a novel glycolysis-related signature to predict the prognosis of patients with breast cancer.World journal of surgical oncology · 2021Article
- Identification of a prognostic ferroptosis-related lncRNA signature in the tumor microenvironment of lung adenocarcinoma.Cell death discovery · 2021Article
- A network approach reveals driver genes associated with survival of patients with triple-negative breast cancer.iScience · 2021Article
- Identification of a Novel Glycolysis-Related Gene Signature for Predicting Breast Cancer Survival.Frontiers in oncology · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer (BC) is one of the most prevalent forms of cancer globally. However, the practical relevance of the RNA expression-based prediction of BC is not clearly understood and requires further study. Using gene expression data downloaded from The Cancer Genome Atlas (TCGA), a risk score staging classification was created using Cox's multiple regression and was used to predict the clinical outcomes of patients with BC. In total, 7 genes, including AC123595.1, leukocyte immunoglobulin-like receptor B5, CD209 molecule, AL049749.1, lymphatic vessel endothelial hyaluronan receptor 1, transmembrane protein 190 and tubulin α 3D chain were identified in association with patient survival. The patients with lower risk scores had considerably improved survival rates than those with higher risk scores. Compared with other clinical factors, the risk score more accurately predicted the clinical outcome of patients with BC. In summary, 7 genes were identified using the Cox regression model, and subsequently used to develop a risk staging model for BC, which may be of use for the medical management of patients.
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